Materials Science and Metallurgy
Associate Professor
Our group develops materials acceleration platforms, often referred to as “self-driving labs.” We are interested in how automation and artificial intelligence can accelerate the design, discovery, and understanding of advanced functional materials.
We study materials for energy conversion and storage, spanning photovoltaics, energy-efficient lighting, and batteries. The group has expertise in inorganic and hybrid framework materials, where we investigate structure–function relationships and explore thermodynamic and kinetic approaches to control material formation, phase transitions, and degradation pathways.
We develop high-throughput methods for the synthesis and characterisation of materials. We are particularly interested in modular and flexible automation, designed to empower scientific creativity through robotics and human-in-the-loop autonomy.
Our research is centred on fostering human-AI-robot collaborations, where scientists’ ability is amplified by artificial intelligence. We design data-driven methods, leveraging machine learning to drive automated experiments, analyse data, and predict reaction outcomes that guide scientific discovery.
